Research Area Specialist Inter (Data Manager/Analyst)

at  University of Michigan

HOW TO APPLY

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

SUMMARY

We are seeking a dedicated and detail-oriented Healthcare Data manager/analyst to join our Family Medicine Q-Trac team at The University of Michigan Department of Family Medicine. In this position, you will play a critical role in supporting our healthcare research efforts by efficiently managing datasets, assisting statisticians, generating insightful visualizations, and contributing to research publications. This position offers an excellent opportunity for a candidate with beginner to intermediate level skills in data management and analysis to make a meaningful impact in the field of healthcare research. One major requirement for this position is the familiarity with REDCAP which is used as the primary tool for managing research data in the department. You will report to our Senior Statistician. You will work on multiple projects and may serve as the primary data manager on large or complex projects. You will develop and execute procedures for organizing, classifying, and reporting on complex information during all of a project?s life cycle.

REQUIRED QUALIFICATIONS*

• Bachelor’s degree in a related field (e.g., statistics, biostatistics, epidemiology, computer science. data science, information science, healthcare management).
• Minimum 4 years of experience in a related field.
• Minimum 1 years of database management experience.
• Strong computing skills.
• Excellent communication and teamwork skills.
• Detail-oriented and able to work independently.
• Eagerness to learn and adapt to new techniques and technologies.
• At least three years of data management programming experience using common data management tools such as REDCAP, SAS, SQL, or Python.
• Experience must demonstrate knowledge of basic programming concepts and include experience combining data from disparate sources, programming reports, cleaning and preparing data for analysis, and debugging data in complex applications.
• Experience querying, managing, and testing data in applications that store data in relational databases, including broad knowledge of relational database concepts.
• Strong organizational skills including experience prioritizing tasks in a fast-paced production environment. This includes the ability to multitask between multiple projects and timelines.

DESIRED QUALIFICATIONS*

• Ability to run basic statistical analyses under the direction of a statistician, including descriptive statistics and hypothesis testing is desired.
• Publication Support: Collaborate with researchers to contribute to the preparation of research papers and publications.
• Data Privacy and Ethics: Knowledge of data privacy regulations (e.g., HIPAA) and ethical considerations in healthcare research is desired.

As a data manger you will:

• Create and maintain databases to organize healthcare-related data using REDCAP.
• Ensure data integrity and quality by performing periodic data cleaning and validation procedures.
• Implement data storage and retrieval solutions for efficient access by the research team.
• Prepare and preprocess healthcare data ready for analysis, including data transformation and standardization.
• Collaborate with statisticians, principal investigators, and other researchers to understand data requirements and objectives.
• Diagnose, identify, and resolve time-sensitive technical or data problems, including programming and procedural errors.
• Establish quality control standards based on project design and need.
• Prepare and document final versions of complex datasets including cleaning, recoding, reformatting, and outputting data (in a variety of formats) as necessary for delivery to key stakeholders.
• Harmonize data with previously collected data or aggregate disparate data sources for analysis and reporting.
• Participate in team meetings, which are pertinent to data aspects of the project.
• Identify opportunities to improve the efficiency and quality of data processing and collaborate with team members to implement solutions.
• Create training materials and general documentation as requested.